GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation
Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli—key functional units of the kidney—from whole slide images (WSIs) in kidney pathology. However, existing open-source tools are often distributed as source code or Docker containers, requiring a...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Journal of Pathology Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2153353925000185 |
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| author | Jialin Yue Tianyuan Yao Ruining Deng Siqi Lu Junlin Guo Quan Liu Juming Xiong Mengmeng Yin Haichun Yang Yuankai Huo |
| author_facet | Jialin Yue Tianyuan Yao Ruining Deng Siqi Lu Junlin Guo Quan Liu Juming Xiong Mengmeng Yin Haichun Yang Yuankai Huo |
| author_sort | Jialin Yue |
| collection | DOAJ |
| description | Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli—key functional units of the kidney—from whole slide images (WSIs) in kidney pathology. However, existing open-source tools are often distributed as source code or Docker containers, requiring advanced programming skills that hinder accessibility for non-programmers, such as clinicians. Additionally, current models are typically trained on a single dataset and lack flexibility in adjusting confidence levels for predictions. To overcome these challenges, we introduce GloFinder, a QuPath plugin designed for single-click automated glomerular detection across entire WSIs with online editing through the graphical user interface. GloFinder employs CircleNet, an anchor-free detection framework utilizing circle representations for precise object localization, with models trained on approximately 160,000 manually annotated glomeruli. To further enhance accuracy, the plugin incorporates weighted circle fusion—an ensemble method that combines confidence scores from multiple CircleNet models to produce refined predictions, achieving superior performance in glomerular detection. GloFinder enables direct visualization and editing of results in QuPath, facilitating seamless interaction for clinicians and providing a powerful tool for nephropathology research and clinical practice. |
| format | Article |
| id | doaj-art-01c2488a3a5d45ed9f1ac0bce25ef0a7 |
| institution | Kabale University |
| issn | 2153-3539 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Pathology Informatics |
| spelling | doaj-art-01c2488a3a5d45ed9f1ac0bce25ef0a72025-08-20T03:53:51ZengElsevierJournal of Pathology Informatics2153-35392025-04-011710043310.1016/j.jpi.2025.100433GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curationJialin Yue0Tianyuan Yao1Ruining Deng2Siqi Lu3Junlin Guo4Quan Liu5Juming Xiong6Mengmeng Yin7Haichun Yang8Yuankai Huo9Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USADepartment of Computer Science, Vanderbilt University, Nashville, TN, USADepartment of Computer Science, Vanderbilt University, Nashville, TN, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USADepartment of Computer Science, Vanderbilt University, Nashville, TN, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USADepartment of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USADepartment of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA; Corresponding author at: Department of Computer Science, Vanderbilt University, Nashville, TN, USA.Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli—key functional units of the kidney—from whole slide images (WSIs) in kidney pathology. However, existing open-source tools are often distributed as source code or Docker containers, requiring advanced programming skills that hinder accessibility for non-programmers, such as clinicians. Additionally, current models are typically trained on a single dataset and lack flexibility in adjusting confidence levels for predictions. To overcome these challenges, we introduce GloFinder, a QuPath plugin designed for single-click automated glomerular detection across entire WSIs with online editing through the graphical user interface. GloFinder employs CircleNet, an anchor-free detection framework utilizing circle representations for precise object localization, with models trained on approximately 160,000 manually annotated glomeruli. To further enhance accuracy, the plugin incorporates weighted circle fusion—an ensemble method that combines confidence scores from multiple CircleNet models to produce refined predictions, achieving superior performance in glomerular detection. GloFinder enables direct visualization and editing of results in QuPath, facilitating seamless interaction for clinicians and providing a powerful tool for nephropathology research and clinical practice.http://www.sciencedirect.com/science/article/pii/S2153353925000185Automated glomerular detectionWhole slide imagesCircleNetWeighted circle fusionQuPath pluginRenal pathology |
| spellingShingle | Jialin Yue Tianyuan Yao Ruining Deng Siqi Lu Junlin Guo Quan Liu Juming Xiong Mengmeng Yin Haichun Yang Yuankai Huo GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation Journal of Pathology Informatics Automated glomerular detection Whole slide images CircleNet Weighted circle fusion QuPath plugin Renal pathology |
| title | GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation |
| title_full | GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation |
| title_fullStr | GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation |
| title_full_unstemmed | GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation |
| title_short | GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation |
| title_sort | glofinder ai empowered qupath plugin for wsi level glomerular detection visualization and curation |
| topic | Automated glomerular detection Whole slide images CircleNet Weighted circle fusion QuPath plugin Renal pathology |
| url | http://www.sciencedirect.com/science/article/pii/S2153353925000185 |
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